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  • 标题:Acquisition of Cooperative Tactics by Soccer Agents with Ability of Prediction and Learning
  • 本地全文:下载
  • 作者:Yoichiro Kumada ; Kazuhiro Ueda
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2001
  • 卷号:16
  • 期号:1
  • 页码:120-127
  • DOI:10.1527/tjsai.16.120
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:Designing soccer agents operating on the Soccer Server has became a standard problem in the multiagent domain, and this paper describes the soccer agents that can learn to make use of cooperative tactics. Considering the ways actual coaches of soccer enable their players learn to execute the soccer tactics, we developed a method of agents’ learning to distinguish good tactics from not-so-good tactics. It is made up mainly of small practical tasks requiring a few agents, of acquisition of appropriate cognitive maps by decomposing the situations into grid information, and of optimization of total play by a kind of adaptive learning. Because the agents perceive the environment as a grid, they have a finite number of condition spaces and are able to predict the behavior of opponents by learning the conditonal probabilities. Each condition has its own utility learned in an evolutionary method.
  • 关键词:soccer agents ; cognitive modeling ; cooperative tactics ; Bayesian prediction ; adaptive learning
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